code: def rfecv_sklearn_example(image="rfecv_sklearn_example.png"):
      X, y = make_classification(
          n_samples=1000,
          n_features=25,
          n_informative=3,
          n_redundant=2,
          n_repeated=0,
          n_classes=8,
          n_clusters_per_class=1,
          random_state=0,
      )
  
      _, ax = plt.subplots()
  
      oz = RFECV(SVC(kernel="linear", C=1), ax=ax)
      oz.fit(X, y)
      oz.show(outpath=os.path.join(IMAGES, image))
  
file_path: yellowbrick/docs/api/model_selection/rfecv.py
imports: import os
  import matplotlib.pyplot
  from sklearn.svm import SVC
  from sklearn.datasets import make_classification
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.model_selection import StratifiedKFold
  from yellowbrick.model_selection import RFECV, rfecv
  from yellowbrick.datasets import load_credit
label_desc: Use image node_id 1 for calling a global function with example usage: rfecv_sklearn_example(image) without return types